Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations879,102
Missing cells0
Missing cells (%)0.0%
Duplicate rows8,759
Duplicate rows (%)1.0%
Total size in memory73.8 MiB
Average record size in memory88.0 B

Variable types

Numeric10

Alerts

Dataset has 8759 (1.0%) duplicate rowsDuplicates
Depth (m) is highly overall correlated with u0 (kPa) and 2 other fieldsHigh correlation
Fr (%) is highly overall correlated with Qtn (-) and 2 other fieldsHigh correlation
Oberhollenzer_classes is highly overall correlated with Qtn (-)High correlation
Qtn (-) is highly overall correlated with Fr (%) and 3 other fieldsHigh correlation
Rf (%) is highly overall correlated with Fr (%) and 1 other fieldsHigh correlation
fs (kPa) is highly overall correlated with Qtn (-) and 1 other fieldsHigh correlation
qc (MPa) is highly overall correlated with Fr (%) and 3 other fieldsHigh correlation
u0 (kPa) is highly overall correlated with Depth (m) and 2 other fieldsHigh correlation
σ',v (kPa) is highly overall correlated with Depth (m) and 2 other fieldsHigh correlation
σ,v (kPa) is highly overall correlated with Depth (m) and 2 other fieldsHigh correlation
Rf (%) is highly skewed (γ1 = 429.8793915) Skewed
Fr (%) is highly skewed (γ1 = 245.8579497) Skewed
Rf (%) has 9057 (1.0%) zeros Zeros
u0 (kPa) has 31650 (3.6%) zeros Zeros
Fr (%) has 8973 (1.0%) zeros Zeros
Oberhollenzer_classes has 78436 (8.9%) zeros Zeros

Reproduction

Analysis started2025-09-17 14:47:37.722698
Analysis finished2025-09-17 14:48:06.601839
Duration28.88 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Depth (m)
Real number (ℝ)

High correlation 

Distinct7384
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.47386
Minimum0.01
Maximum73.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 MiB
2025-09-17T16:48:06.898307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.92
Q14.58
median9.49
Q315.86
95-th percentile30.09
Maximum73.84
Range73.83
Interquartile range (IQR)11.28

Descriptive statistics

Standard deviation9.3284603
Coefficient of variation (CV)0.81301852
Kurtosis4.0382596
Mean11.47386
Median Absolute Deviation (MAD)5.45
Skewness1.5931476
Sum10086693
Variance87.020172
MonotonicityNot monotonic
2025-09-17T16:48:06.973218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.09 488
 
0.1%
1.17 488
 
0.1%
1.26 487
 
0.1%
1.07 487
 
0.1%
0.99 487
 
0.1%
1.16 487
 
0.1%
1.18 487
 
0.1%
1.19 487
 
0.1%
0.65 487
 
0.1%
1.25 487
 
0.1%
Other values (7374) 874230
99.4%
ValueCountFrequency (%)
0.01 461
0.1%
0.02 467
0.1%
0.03 472
0.1%
0.04 476
0.1%
0.05 479
0.1%
0.06 480
0.1%
0.07 481
0.1%
0.08 482
0.1%
0.09 481
0.1%
0.1 477
0.1%
ValueCountFrequency (%)
73.84 1
< 0.1%
73.83 1
< 0.1%
73.82 1
< 0.1%
73.81 1
< 0.1%
73.8 1
< 0.1%
73.79 1
< 0.1%
73.78 1
< 0.1%
73.77 1
< 0.1%
73.76 1
< 0.1%
73.75 1
< 0.1%

qc (MPa)
Real number (ℝ)

High correlation 

Distinct7068
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2331517
Minimum-0.2
Maximum101.73
Zeros4667
Zeros (%)0.5%
Negative4265
Negative (%)0.5%
Memory size13.4 MiB
2025-09-17T16:48:07.055309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.2
5-th percentile0.29
Q10.94
median2.14
Q35.75
95-th percentile21.61
Maximum101.73
Range101.93
Interquartile range (IQR)4.81

Descriptive statistics

Standard deviation8.3875147
Coefficient of variation (CV)1.6027654
Kurtosis16.320877
Mean5.2331517
Median Absolute Deviation (MAD)1.55
Skewness3.5977723
Sum4600474.1
Variance70.350402
MonotonicityNot monotonic
2025-09-17T16:48:07.127474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4667
 
0.5%
0.92 3865
 
0.4%
0.91 3599
 
0.4%
0.94 3585
 
0.4%
0.93 3566
 
0.4%
0.9 3528
 
0.4%
1 3471
 
0.4%
1.04 3457
 
0.4%
0.95 3457
 
0.4%
0.97 3412
 
0.4%
Other values (7058) 842495
95.8%
ValueCountFrequency (%)
-0.2 1
 
< 0.1%
-0.19 14
 
< 0.1%
-0.18 31
 
< 0.1%
-0.17 11
 
< 0.1%
-0.16 8
 
< 0.1%
-0.15 12
 
< 0.1%
-0.14 10
 
< 0.1%
-0.13 72
< 0.1%
-0.12 94
< 0.1%
-0.11 94
< 0.1%
ValueCountFrequency (%)
101.73 1
< 0.1%
101.1 1
< 0.1%
101.02 1
< 0.1%
97.08 1
< 0.1%
95.84 1
< 0.1%
95.51 1
< 0.1%
95.2 1
< 0.1%
94.94 1
< 0.1%
94.89 1
< 0.1%
94.78 1
< 0.1%

fs (kPa)
Real number (ℝ)

High correlation 

Distinct9561
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.702243
Minimum-99.9
Maximum1389.6
Zeros6185
Zeros (%)0.7%
Negative8488
Negative (%)1.0%
Memory size13.4 MiB
2025-09-17T16:48:07.194744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-99.9
5-th percentile4.7
Q116
median31.4
Q364.9
95-th percentile182
Maximum1389.6
Range1489.5
Interquartile range (IQR)48.9

Descriptive statistics

Standard deviation71.306747
Coefficient of variation (CV)1.3035434
Kurtosis23.011209
Mean54.702243
Median Absolute Deviation (MAD)19.2
Skewness3.8532624
Sum48088851
Variance5084.6522
MonotonicityNot monotonic
2025-09-17T16:48:07.270525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6185
 
0.7%
11 2061
 
0.2%
15.9 2054
 
0.2%
14.3 2000
 
0.2%
12.1 1963
 
0.2%
14.8 1957
 
0.2%
13.2 1945
 
0.2%
12.4 1940
 
0.2%
12.6 1935
 
0.2%
13.1 1917
 
0.2%
Other values (9551) 855145
97.3%
ValueCountFrequency (%)
-99.9 1
< 0.1%
-99.8 1
< 0.1%
-99.7 1
< 0.1%
-98.4 2
< 0.1%
-98.1 1
< 0.1%
-97.7 1
< 0.1%
-97.4 1
< 0.1%
-97.3 1
< 0.1%
-97.1 1
< 0.1%
-96.5 1
< 0.1%
ValueCountFrequency (%)
1389.6 1
 
< 0.1%
1191.2 2
< 0.1%
1154.8 2
< 0.1%
1150.5 2
< 0.1%
1118.5 3
< 0.1%
1109.7 2
< 0.1%
1098.7 2
< 0.1%
1087.9 2
< 0.1%
1074.4 2
< 0.1%
1056.4 1
 
< 0.1%

Rf (%)
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct6715
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5334677
Minimum-100
Maximum22000
Zeros9057
Zeros (%)1.0%
Negative11532
Negative (%)1.3%
Memory size13.4 MiB
2025-09-17T16:48:07.347545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile0.2
Q10.7
median1.4
Q32.58
95-th percentile7.03
Maximum22000
Range22100
Interquartile range (IQR)1.88

Descriptive statistics

Standard deviation37.958935
Coefficient of variation (CV)14.982995
Kurtosis220754.81
Mean2.5334677
Median Absolute Deviation (MAD)0.84
Skewness429.87939
Sum2227176.5
Variance1440.8807
MonotonicityNot monotonic
2025-09-17T16:48:07.423386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9057
 
1.0%
0.36 3921
 
0.4%
0.37 3921
 
0.4%
0.4 3902
 
0.4%
0.39 3885
 
0.4%
0.34 3848
 
0.4%
0.41 3842
 
0.4%
0.33 3802
 
0.4%
0.35 3802
 
0.4%
0.42 3775
 
0.4%
Other values (6705) 835347
95.0%
ValueCountFrequency (%)
-100 10
< 0.1%
-98.95 1
 
< 0.1%
-98.82 1
 
< 0.1%
-98.77 1
 
< 0.1%
-98.66 1
 
< 0.1%
-98.55 1
 
< 0.1%
-97.66 1
 
< 0.1%
-97.3 10
< 0.1%
-97.17 1
 
< 0.1%
-97.05 1
 
< 0.1%
ValueCountFrequency (%)
22000 1
< 0.1%
19333.33 1
< 0.1%
12200 1
< 0.1%
8900 1
< 0.1%
3906.58 1
< 0.1%
3284.09 1
< 0.1%
3009.87 1
< 0.1%
2822.63 1
< 0.1%
2425.93 1
< 0.1%
2400 2
< 0.1%

σ,v (kPa)
Real number (ℝ)

High correlation 

Distinct7583
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.00334
Minimum0.19
Maximum1402.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 MiB
2025-09-17T16:48:07.490404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.19
5-th percentile17.48
Q187.02
median180.31
Q3301.34
95-th percentile571.71
Maximum1402.96
Range1402.77
Interquartile range (IQR)214.32

Descriptive statistics

Standard deviation177.24075
Coefficient of variation (CV)0.81301854
Kurtosis4.0382587
Mean218.00334
Median Absolute Deviation (MAD)103.55
Skewness1.5931475
Sum1.9164717 × 108
Variance31414.285
MonotonicityNot monotonic
2025-09-17T16:48:07.565382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.71 488
 
0.1%
22.23 488
 
0.1%
15.2 487
 
0.1%
23.94 487
 
0.1%
22.61 487
 
0.1%
22.04 487
 
0.1%
12.35 487
 
0.1%
18.62 487
 
0.1%
18.81 487
 
0.1%
15.01 487
 
0.1%
Other values (7573) 874230
99.4%
ValueCountFrequency (%)
0.19 461
0.1%
0.38 467
0.1%
0.57 472
0.1%
0.76 476
0.1%
0.95 479
0.1%
1.14 480
0.1%
1.33 481
0.1%
1.52 482
0.1%
1.71 481
0.1%
1.9 477
0.1%
ValueCountFrequency (%)
1402.96 1
< 0.1%
1402.77 1
< 0.1%
1402.58 1
< 0.1%
1402.39 1
< 0.1%
1402.2 1
< 0.1%
1402.01 1
< 0.1%
1401.82 1
< 0.1%
1401.63 1
< 0.1%
1401.44 1
< 0.1%
1401.25 1
< 0.1%

u0 (kPa)
Real number (ℝ)

High correlation  Zeros 

Distinct7615
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.65425
Minimum0
Maximum724.37
Zeros31650
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size13.4 MiB
2025-09-17T16:48:07.638662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.55
Q138.36
median86.23
Q3147.84
95-th percentile286.94
Maximum724.37
Range724.37
Interquartile range (IQR)109.48

Descriptive statistics

Standard deviation91.041473
Coefficient of variation (CV)0.8616925
Kurtosis4.3370831
Mean105.65425
Median Absolute Deviation (MAD)53.07
Skewness1.6355718
Sum92880860
Variance8288.5498
MonotonicityNot monotonic
2025-09-17T16:48:07.733286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31650
 
3.6%
7.55 489
 
0.1%
3.73 488
 
0.1%
12.46 488
 
0.1%
7.65 488
 
0.1%
7.75 488
 
0.1%
12.26 488
 
0.1%
12.36 488
 
0.1%
7.36 488
 
0.1%
4.22 487
 
0.1%
Other values (7605) 843060
95.9%
ValueCountFrequency (%)
0 31650
3.6%
0.1 466
 
0.1%
0.2 471
 
0.1%
0.29 475
 
0.1%
0.39 478
 
0.1%
0.49 481
 
0.1%
0.59 483
 
0.1%
0.69 484
 
0.1%
0.78 484
 
0.1%
0.88 483
 
0.1%
ValueCountFrequency (%)
724.37 1
< 0.1%
724.27 1
< 0.1%
724.17 1
< 0.1%
724.08 1
< 0.1%
723.98 1
< 0.1%
723.88 1
< 0.1%
723.78 1
< 0.1%
723.68 1
< 0.1%
723.59 1
< 0.1%
723.49 1
< 0.1%

σ',v (kPa)
Real number (ℝ)

High correlation 

Distinct36679
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.34918
Minimum0.09
Maximum678.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 MiB
2025-09-17T16:48:07.810250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile9.56
Q146.87
median94.2
Q3154.97
95-th percentile287.83
Maximum678.59
Range678.5
Interquartile range (IQR)108.1

Descriptive statistics

Standard deviation88.351238
Coefficient of variation (CV)0.78639861
Kurtosis3.3647668
Mean112.34918
Median Absolute Deviation (MAD)52.59
Skewness1.4751583
Sum98766388
Variance7805.9412
MonotonicityNot monotonic
2025-09-17T16:48:07.887233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.4 482
 
0.1%
5.7 482
 
0.1%
11.21 481
 
0.1%
5.51 481
 
0.1%
8.55 481
 
0.1%
8.36 479
 
0.1%
2.85 478
 
0.1%
14.06 477
 
0.1%
16.91 477
 
0.1%
19.76 472
 
0.1%
Other values (36669) 874312
99.5%
ValueCountFrequency (%)
0.09 355
< 0.1%
0.18 360
< 0.1%
0.19 106
 
< 0.1%
0.28 364
< 0.1%
0.37 367
< 0.1%
0.38 107
 
< 0.1%
0.46 370
< 0.1%
0.55 372
< 0.1%
0.57 108
 
< 0.1%
0.64 373
< 0.1%
ValueCountFrequency (%)
678.59 1
< 0.1%
678.5 1
< 0.1%
678.41 1
< 0.1%
678.31 1
< 0.1%
678.22 1
< 0.1%
678.13 1
< 0.1%
678.04 1
< 0.1%
677.95 1
< 0.1%
677.85 1
< 0.1%
677.76 1
< 0.1%

Qtn (-)
Real number (ℝ)

High correlation 

Distinct57516
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.494711
Minimum-127.57
Maximum1001
Zeros12
Zeros (%)< 0.1%
Negative13535
Negative (%)1.5%
Memory size13.4 MiB
2025-09-17T16:48:07.966800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-127.57
5-th percentile1.78
Q15.61
median25.02
Q365.79
95-th percentile308.24
Maximum1001
Range1128.57
Interquartile range (IQR)60.18

Descriptive statistics

Standard deviation124.02582
Coefficient of variation (CV)1.8375636
Kurtosis17.96685
Mean67.494711
Median Absolute Deviation (MAD)21.46
Skewness3.8087213
Sum59334736
Variance15382.405
MonotonicityNot monotonic
2025-09-17T16:48:08.040109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001 1957
 
0.2%
1.98 821
 
0.1%
1.97 814
 
0.1%
1.91 788
 
0.1%
1.99 782
 
0.1%
2.04 777
 
0.1%
2.03 774
 
0.1%
1.89 770
 
0.1%
1.95 766
 
0.1%
1.9 763
 
0.1%
Other values (57506) 870090
99.0%
ValueCountFrequency (%)
-127.57 1
< 0.1%
-84.77 1
< 0.1%
-80.78 1
< 0.1%
-76.06 1
< 0.1%
-68.47 1
< 0.1%
-58.36 1
< 0.1%
-55.14 1
< 0.1%
-53.94 1
< 0.1%
-53.21 1
< 0.1%
-52.48 1
< 0.1%
ValueCountFrequency (%)
1001 1957
0.2%
999.79 2
 
< 0.1%
999.51 1
 
< 0.1%
999.48 1
 
< 0.1%
999.27 1
 
< 0.1%
999.09 1
 
< 0.1%
999.03 1
 
< 0.1%
998.99 1
 
< 0.1%
998.87 1
 
< 0.1%
998.81 1
 
< 0.1%

Fr (%)
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct10283
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.762247
Minimum-100
Maximum33166.67
Zeros8973
Zeros (%)1.0%
Negative13968
Negative (%)1.6%
Memory size13.4 MiB
2025-09-17T16:48:08.113344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile0.19
Q10.75
median1.68
Q33.39
95-th percentile8.85
Maximum33166.67
Range33266.67
Interquartile range (IQR)2.64

Descriptive statistics

Standard deviation87.898839
Coefficient of variation (CV)23.363389
Kurtosis73671.775
Mean3.762247
Median Absolute Deviation (MAD)1.14
Skewness245.85795
Sum3307398.9
Variance7726.206
MonotonicityNot monotonic
2025-09-17T16:48:08.281399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8973
 
1.0%
0.37 3870
 
0.4%
0.36 3728
 
0.4%
0.33 3677
 
0.4%
0.38 3652
 
0.4%
0.4 3608
 
0.4%
0.35 3602
 
0.4%
0.34 3599
 
0.4%
0.39 3542
 
0.4%
0.45 3525
 
0.4%
Other values (10273) 837326
95.2%
ValueCountFrequency (%)
-100 2
< 0.1%
-99.95 1
< 0.1%
-99.48 1
< 0.1%
-99.34 1
< 0.1%
-99.28 1
< 0.1%
-99.26 1
< 0.1%
-99.04 1
< 0.1%
-98.96 1
< 0.1%
-98.84 1
< 0.1%
-98.83 1
< 0.1%
ValueCountFrequency (%)
33166.67 1
< 0.1%
31777.78 1
< 0.1%
27500 1
< 0.1%
26000 1
< 0.1%
20260.87 1
< 0.1%
18000 1
< 0.1%
17162.79 1
< 0.1%
16400 1
< 0.1%
14113.21 1
< 0.1%
13777.78 1
< 0.1%

Oberhollenzer_classes
Real number (ℝ)

High correlation  Zeros 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4036494
Minimum0
Maximum7
Zeros78436
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size13.4 MiB
2025-09-17T16:48:08.343108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.2846546
Coefficient of variation (CV)0.51880937
Kurtosis-0.79009516
Mean4.4036494
Median Absolute Deviation (MAD)1
Skewness-0.72467407
Sum3871257
Variance5.2196464
MonotonicityNot monotonic
2025-09-17T16:48:08.388234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 208247
23.7%
6 180407
20.5%
7 163684
18.6%
1 99211
11.3%
4 98749
11.2%
0 78436
 
8.9%
2 43519
 
5.0%
3 6849
 
0.8%
ValueCountFrequency (%)
0 78436
 
8.9%
1 99211
11.3%
2 43519
 
5.0%
3 6849
 
0.8%
4 98749
11.2%
5 208247
23.7%
6 180407
20.5%
7 163684
18.6%
ValueCountFrequency (%)
7 163684
18.6%
6 180407
20.5%
5 208247
23.7%
4 98749
11.2%
3 6849
 
0.8%
2 43519
 
5.0%
1 99211
11.3%
0 78436
 
8.9%

Interactions

2025-09-17T16:48:02.048023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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Correlations

2025-09-17T16:48:08.439178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Depth (m)Fr (%)Oberhollenzer_classesQtn (-)Rf (%)fs (kPa)qc (MPa)u0 (kPa)σ',v (kPa)σ,v (kPa)
Depth (m)1.0000.0870.475-0.472-0.037-0.0420.0200.9780.9831.000
Fr (%)0.0871.0000.311-0.5370.9430.106-0.6190.0950.0780.087
Oberhollenzer_classes0.4750.3111.000-0.5180.205-0.223-0.3310.4590.4730.475
Qtn (-)-0.472-0.537-0.5181.000-0.4190.5690.828-0.461-0.468-0.472
Rf (%)-0.0370.9430.205-0.4191.0000.205-0.555-0.026-0.045-0.037
fs (kPa)-0.0420.106-0.2230.5690.2051.0000.629-0.052-0.035-0.042
qc (MPa)0.020-0.619-0.3310.828-0.5550.6291.0000.0040.0300.020
u0 (kPa)0.9780.0950.459-0.461-0.026-0.0520.0041.0000.9240.978
σ',v (kPa)0.9830.0780.473-0.468-0.045-0.0350.0300.9241.0000.983
σ,v (kPa)1.0000.0870.475-0.472-0.037-0.0420.0200.9780.9831.000

Missing values

2025-09-17T16:48:05.413979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-09-17T16:48:05.747068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Depth (m)qc (MPa)fs (kPa)Rf (%)σ,v (kPa)u0 (kPa)σ',v (kPa)Qtn (-)Fr (%)Oberhollenzer_classes
14865100.010.000.000.000.190.100.09-27.090.004.0
14865110.020.000.000.000.380.200.18-14.580.004.0
14865120.030.000.000.000.570.290.28-10.410.004.0
14865130.040.000.000.000.760.390.37-8.320.004.0
14865140.050.000.000.000.950.490.46-7.070.004.0
14865150.060.000.00-0.011.140.590.55-6.240.004.0
14865160.070.000.00-0.011.330.690.64-5.64-0.014.0
14865170.080.000.00-0.011.520.780.74-5.20-0.014.0
14865180.090.000.00-0.011.710.880.83-4.85-0.014.0
14865190.100.000.00-0.021.900.980.92-4.57-0.014.0
Depth (m)qc (MPa)fs (kPa)Rf (%)σ,v (kPa)u0 (kPa)σ',v (kPa)Qtn (-)Fr (%)Oberhollenzer_classes
25169699.7744.1779.900.22185.6371.32114.31409.960.221.0
25169709.7844.37105.500.14185.8271.42114.40427.650.141.0
25169719.7946.080.000.08186.0171.51114.50440.750.081.0
25169729.8047.790.000.00186.2071.61114.59413.800.001.0
25169739.8148.940.000.00186.3971.71114.68423.670.001.0
25169749.8249.590.000.00186.5871.81114.77431.220.001.0
25169759.8350.510.000.00186.7771.91114.86446.310.001.0
25169769.8454.250.000.00186.9672.01114.95461.360.001.0
25169779.8554.910.000.00187.1572.10115.05473.500.001.0
25169789.8654.830.000.00187.3472.20115.14474.780.001.0

Duplicate rows

Most frequently occurring

Depth (m)qc (MPa)fs (kPa)Rf (%)σ,v (kPa)u0 (kPa)σ',v (kPa)Qtn (-)Fr (%)Oberhollenzer_classes# duplicates
280.010.340.000.000.190.100.091001.000.000.05
110.010.090.000.000.190.100.091001.000.000.04
130.010.120.000.000.190.100.091001.000.000.04
1040.040.480.000.000.760.390.371001.000.000.04
00.010.000.000.000.190.100.09-44.500.000.03
50.010.000.000.000.190.100.096.640.000.03
190.010.230.000.000.190.100.091001.000.000.03
210.010.280.000.000.190.100.091001.000.000.03
390.010.630.000.000.190.100.091001.000.000.03
460.020.000.000.000.380.200.182.290.000.03